Optimize your product or process with Design of Experiments (DOE)
Design-Expert® software, version 8 (DX8) offers features you won't find anywhere else in an incredibly easy-to-use format. This powerful program is a must for anyone wanting to improve a process or a product. With Design-Expert you can screen for vital factors, locate ideal process settings to achieve peak performance and discover your optimal product formulations.

Design-Expert offers an impressive array of design options. Design Expert 8 provides great flexibility to handle categorical factors and allows them to be combined with mixture and/or process variables. After building your design, generate worksheets with your experiments laid out for you in randomized run-order. Add, delete or duplicate runs in any design with the handy design editor.

With annotated statistical analysis and an extensive context-sensitive help system, you can easily interpret the outputs. Interactive 2-D graphics support use of your mouse to drag contours or set flags that display coordinates and predicted responses. Rotatable 3-D plots make response visualization easy.

With the powerful optimization features in Design-Expert, you can maximize desirability for dozens of responses simultaneously. There are also unique tools for generating and graphing propagation of error (POE), thus allowing you to achieve six-sigma objectives for reducing variation. Maximize, minimize or hit targets with factor levels set to give you robust results.

The upgrade to version 8 offers powerful new statistical tools, such as upfront power calculation for factorial designs and the Fraction of Design Space (FDS) graph for design evaluation. Other new features for ease-of-use, functionality, and power add extra appeal to a long-standing and well-loved program.

Design Expert Features

Powerful, Yet Easy to Use

Designed as a specialized DOE software package, Design-Expert 6 offers features for ease of use, functionality and power that you won't find in general statistical packages. You'll discover a wide variety of designs, the flexibility to modify designs, unique evaluation capabilities, tools for response modeling, graphics to simplify interpretation, multiple response optimization, POE capabilities, an intuitive interface and a greatly expanded help system.

The factorial design builder makes it easy to set up screening studies. Color-coded choices provide valuable information on experiment resolution.

Crossed Mixture-Process Design - Seven Blends (on Triangles) at Eight Process Combinations (Cube).

A Tremendous Variety of Designs Meet All Your Experimental Needs

• Standard two-level full and fractional factorials (up to 512 runs) for testing up to 21 factors simultaneously, now also with minimum-aberration blocking choices
• General (multilevel) factorial designs (up to 32,000 runs) using factors with mixed levels
• Taguchi orthogonal arrays
• High-resolution irregular fractions, such as 4 factors in 12 runs
• Placket-Burman designs for 11, 19, 23, 27 or 31 factors in 12, 20, 24, 28, 32 or 64 runs respectively
• “Min-Run Res IV” (two-level factorial) designs for 5 to 50 factors: Screen main effects with maximum efficiency in terms of experimental runs.
• Response Surface Method (RSM) designs, including central composite (small, face-centered, etc.), Box- Behnken (3-level), hybrid and D-Optimal
• Mixture designs, such as simplex-lattice, simplex-centroid screening (for up to 24 components) and D-optimal
• Combined mixture and process designs (mix your cake and bake it, too!)
• Ability to graph any two columns of data on the XY graph (this is a great way to view a blocked effect)
• Easy-to-use automatic or manual model reduction
• Ability to easily analyze designs with botched or missing data

High-powered mixture design and analysis features lead you to optimal formulations.

Enjoy Incredible Flexibility in Design Modification

• Define your own generators for fractional factorial designs
• Impose linear multivariable constraints on RSM or mixture designs
• Add categorical factors to RSM, mixture or combined designs
• Create a factorial candidate set for RSM designs when only specific factor levels are available
• Ignore a row of data while preserving the numbers

Build Confidence with Statistical Analysis of Data

• If your model is aliased, a warning will pop up prior to viewing the ANOVA for two-level fractional factorials, allowing you to make substitutions for aliased effects
• Select optional annotated views for assistance interpreting the ANOVA
• Inspect F-test values on individual model terms and confidence intervals on coefficients
• Automatically select effects using Lenth's criteria or probability values
• Take advantage of new user preferences, for example, make a global change in the significance threshold (0.05 by default vs. 0.01 and 0.1)

Take Advantage of Powerful Tools for Response Modeling

• Change models from RSM to factorial and back and from Scheffe (mixture) to slack (during design building and at model selection)
• Add integer power terms to the model, for example, quartic
• Select terms for model, error, or to be ignored (allows analysis of split-plot and nested designs)

Simplify Interpretation with Terrific Graphics

• A quick summary of the design type as well as factor, response and model information is available by clicking on the design status node
• Discover significant effects at a glance with half-normal or normal probability plots, made easier by including points representing estimates of pure error (if available from your design)
• See the Box-Cox plot for advice on the best response transformation
• View a complete array of diagnostic graphs to check statistical assumptions and detect possible outliers (bonus feature: predicted-versus-actual graphs with a 45º line)
• Graph alternative aliased interactions
• See the effects plot in the original scale after transforming the response
• Observe variation in predictions by viewing the least significant difference (LSD) bars on the model graphs
• Poorly predicted regions on contour maps are shaded to give you confidence in your predictions
• Slice your contour plots using a simple slide bar (and see actual design points when they're on a slice!)
• Set flags to reveal the predicted response at any location
• Drag 2-D contours using your mouse
• Rotate 3-D graphics and see projected 2-D contours
• Edit colors, text and more to produce professional reports
• See all effects on one graph with trace and perturbation plots
• Plot the standard error of your design on any graph type (contour, 3-D, etc.)

Brilliant graphics help you visualize response surface optimization. Real-time rotation allows fast viewing with minimal effort.

Vital factors pop out on Half-Normal Plots. Discover critical interactions affecting your product or process.

Drag contours and set flags to predict responses at any combination of factors.

Locate Your Sweet Spot with Multiple Response Optimization

• Maximize, minimize or target specific levels for both responses and factors
• Set weight and importance levels to prioritize responses for desirability
• Choose 2-D contour, 3-D surface, histogram or ramp desirability graphs
• Include categorical factors
• Set factors at constant levels
• Add equation-only responses, such as cost, to the optimization process
• Look at the overlay plot to view constraints on your process or formulation
• Predict responses at any set of conditions (including confidence levels)
• Discover optimal process conditions or formulations

Achieve "Six-Sigma" Goals

• Explore propagation of error (POE) for mixtures, crossed designs and transformed responses, as well as RSM
• For purposes of POE, enter your own response standard deviation or set it at zero

Save Time with Design-Expert's Intuitive Interface

• Easily maneuver through the program: down trees, through wizards, and across progressive toolbars
• Quickly select the next step with incredibly easy-to-use push-buttons
• Open reports and graphs for automatic updating
• View numerical outputs spreadsheet style
• Cut and paste graphics to your word processor or presentation, or numbers to and from a spreadsheet
• Export any grid view as ASCII text, for example, design layouts or ANOVA reports
• View several graphs simultaneously using the handy pop-out option
• 32-bit architecture provides maximum performance on Windows 95, 98, 2000, NT and beyond
• Access graphic and spreadsheet options instantly with a simple right click
• Choose significant terms to plot from the pull-down list on the Factors Tool

Find the Answers to your Questions in the Expanded Help System (All new!)

• Greatly improved context-sensitive help provides immediate response
• Better guidance helps you choose the best model
• A bonus help section provides "quick start" advice to novices
• Special user tips offer hints not normally found in help systems

Interactions like this are often the key to breakthrough discoveries. Go for the maximum combination or find the flats for robust operation.

Graphical optimization shows clear windows for multiple response optimization.

What's New in Design Expert 8

New graphics and improved interface

• Half-normal selection of important effects on all factorial designs*:
  Simple and robust method for selecting important effects – formerly available only for two-level designs. For example, the screen shot to the right is from an experiment on 5 woods glued with 5 adhesives, using 2 applicators with 4 clamps at 2 pressures. The vital effects become apparent at a glance!
  *(Detailed in "Graphical Select-ion of Effects in General Factorials"–winner of the Shewell Award for best presentation at the 2007 Fall Technical Conference, co-sponsored by the American Society for Quality and the American Statistical Association.)
• Smoother color gradations on 2D contours: More impressive for presentations to management, clients, or colleagues.
• Rounded contour values: More presentable defaults requiring less 'fiddling' for reporting purposes.
• Plant flags on 3D surfaces: Previously, you could only put flags on 2D contour plots. To the right we see a flag planted by numerical optimization on turbidity of a detergent formulation via mixture design – a specialized application of response surface methods (RSM).
• New and fully configurable mesh option that reflects smooth, lighted colors off your 3D surface: Dazzle your customers and colleagues while providing highly-informative graphics showing how responses will react to process changes. (Mesh can be turned off if you like.)
• 3D graphs that you can spin with your mouse: When you see your cursor turn into a hand (I), simply grab and rotate! Double-click the graph to go back to the starting angle.
• Push-button averaging on the factors tool: Provides far easier main effects plotting and makes interactions more meaningful. Previously, the only option to average factors came via a hidden drop-list. The screen shot series at right shows the result of simply pressing the "Avg" for 5 woods glued with 5 adhesives using 2 applicators at 2 pressures. This causes the least significant difference (LSD) bars to shrink, revealing an important difference between two particular clamps.
• More-interactive cube plots: Click on design points to see factor levels and response predictions on graph legends, as below.
• Direct setting of discrete (fixed) numeric levels in response surface designs: Limit factor settings to reasonable levels but still produce continuous models. The example to the right shows that 3 battery types must be tested at 3 discrete temperatures. Previously, this would have been possible but very tricky via a work-around. Now it's easy!
• Discrete factor levels adhered to in numeric optimization: Find the most desirable setting for factors that are not continuous, such as the number of passes through a spray coater.
• Enter input variables vertically (as shown above): When entering many levels, this may be more convenient than the horizontal layout.
• Reference lines on plots: Horizontal, vertical, and free style-lines enhance plots. At the right it becomes completely clear that four clamps tested for a wood-adhesive application fall into two distinct groups – acceptable versus not acceptable, based on a cutoff of 50.
• Predicted vs. Actual graph availability in Model Graphs, not just in Diagnostics: This is useful when a response has been transformed because in Model Graphs mode, you can change the view back to the more relevant original scale.
• Confidence, prediction, and tolerance intervals (CI, PI & TI) plotted with configurable colors in one-factor response plots: Convey prediction uncertainties via bands around the best fit. The screen shot at right shows actual run results represented as red circles. The solid line is the predicted value based on the polynomial model. The bands are the CI (narrowest), PI, and TI (widest).
• Color-coded response surface graphs show where standard error increases: This makes it easier to understand why a predicted response will get you in trouble by extrapolating beyond actual experimentation regions. The example at right shows a flag set beyond the axial points of a central composite design-making the prediction meaningless.

Better mixture design and modeling tools

• Partial quadratic mixture (PQM) analysis: Model non-linear blending behavior most effectively. The example at right shows an orange drink formulated using artificial flavorings. Primary taste intensity, as measured by a sensory panel, proves to be non-linear in a way that is modeled best using PQM.
• Design for linear plus squared terms in mixture models: Reduce the number of blends required for optimally-designed experiments that reveal non-linear blending.
• Design for special and full quartic mixture models: Capture extremely non-linear relationships among all components.
• Blocking expanded to simplex mixture designs: For example, blend your cakes and bake them in two oven batches.
• Trace plot options show end points as actual values when building designs using U-pseudo coding: The upper ("U") bounded approach is advantageous when inverting regions in certain constrained mixture situations. However, due to axis flipping, it's easy to misinterpret trends when viewing a trace plot without this new feature.
• Increased limit on components for screening and historical* designs. Design-Expert now handles up to 50 individual ingredients – up from 40 and 24, respectively.
  *(An example is happenstance data collected by assaying retained samples from a period of material production.)

More choices when custom-designing your experiment

• D-, IV-, and A-optimal design selection: New and expanded criteria when crafting experiments to models of choice within realistic constraints.
• Constraints calculator: Simplifies derivation of constraint inequalities. At right, food scientists cooking starch must bake it longer at low temperatures. With program Help guidance, the design space's lower left corner can be excluded using a multilinear constraint equation generated from a few user inputs. An optimal design is then fitted to this region.
• Tolerance-interval-based design sizing: Enhances your fraction of design space (fds) plots to assess whether your planned experiment is large enough, given the underlying variability (noise), to establish tolerances within the acceptable range.

Additional statistics and more concise reporting of vital results

• Improved curvature testing for factorials with center points: All design points are now fitted to the polynomial model used for predictions. This provides a more realistic impact of significant non-linear response behavior. Diagnostics can be done for the model adjusted for curvature or, via a view option, unadjusted. Models without a term for curvature (unadjusted) are used for model graph and point predictions.
• Coefficients summary: After modeling your response(s), see a concise table of coefficients that's color-coded by relative significance. Below, the second response is modeled only by main effects, two being significant at the p<0.1 level.
• Condensed "Fit Summary" table: See vital details on model choices before delving into all the particulars. Below you can see why the program recommends one model over others (note the superior R-squared values for quadratic).
• Tolerance interval (TI) estimates on point prediction: This is important for verification studies to ensure your process stays within manufacturing specifications. For example, the TI shown below provides assurance that thickness will remain within a required range of 4400 to 4600.

Increased visibility and versatility of tools and features

• Many new, high-visibility tools: Options previously available via hidden View menu options are now easily seen and capitalized upon. The Design Tool shown 'floating' on the screen shot below is one example.
• Design layout column widths now adjust automatically by double-clicking column-header boundaries: Multiple columns adjust simultaneously!
• Attach row comments by right-clicking on row headers: A handy way to record important observations, as shown below.
• Topic Help, Tutorials, and Sample Files now also reside in the main Help menu: Follow these alternate paths for getting timely program advice.
• Screen Tips is now a main menu item ("Tips"): Great visibility and easy access to very useful just-in-time advice, shown below.
• Response surface method (RSM) models can be fitted with factors in their actual levels: This enables no-intercept model functionality.

Enhanced design evaluation

• Several new matrix measures are now provided: Most notable is the G-efficiency. (This criterion, expressed on a 0 to 100 percent scale with higher being better, leads to designs that generate more consistent variance of your predicted response. However, like any other single measure, it may not accurately reflect the overall effectiveness of a particular matrix. That's why Design-Expert provides an array of matrix statistics and graphics for overall design evaluation.)
• Fraction of paired design space (FPDS): This resourceful tool lets you assess the power of RSM or mixture designs to detect specified signals (response differences judged important) in the presence of noise (system-standard deviation). At right, less than half the design space reveals the difference of interest. Ideally, this exceeds 80 percent, so here the experimenter should consider adding more runs to the design.
• New, powerful tools for multiple response optimization: Options include standard error models. All else equal, choose system settings in regions predicted to exhibit the highest precision.

Many things made nicer, easier faster throughout the program

• One-click updates: Check for free releases with one press (shown at right) and download them directly.
• Better defaults and tick marks: Nicely rounded values provide presentable graphs straight away.
• Zoom up graphs with your mouse wheel (a right-click resets to original size): Quickly zero in on regions of interest.
• Hold down your left mouse button to drag graphs into various positions (a right-click resets original placement): It's a fast way to situate the region of interest where you want it in the coordinate space. Components G and H in the mixture trace plot at right are constrained to very tight ranges relative to other ingredients. They are hardly visible without first zooming and then dragging the intersection (the overall centroid of the formulation space) to the middle.
• Separate preference tabs for X-Y versus surface graphs: DX8 delivers plotting and graphing simplicity.
• Reduced graph-updating flicker: Now it's less distracting when you redraw responses at varying input-variable levels.
• Categoric factors (established via general factorials, for example) are now convertible to discrete numerics: This lets you apply response surface methodologies while adhering to processes that run most conveniently only at specific settings.
• Color-by-point-type added to graph columns: Very useful addition to scatter-plots, such as this one below for a central composite design (CCD).
• Upgraded MFC (Microsoft Foundation Class) common controls: This new application framework provides an improved look and feel.
• XML utility offers new script feature that lists all possible commands. You can parse files with extensions other than .xml. It also provides new import/export/reset-preference commands: More power to operate Design-Expert programmatically.